In manufacturing casting/molding processes, for product quality of the molded article, it is of importance to optimize the mold design and the process conditions. Conventionally, such optimization is attained after many trial and error experiments which are repeated on the basis of the rule of thumb of an expert. With the advance in computer technology, it has become possible to analyze flow behavior of a material during a casting/molding process by computer simulation. When realistically modeled, the results from such simulation may be used to predict the casting behavior, thereby improving the efficiency of product and mold-design, and optimization of processing conditions.
Conventional methods for simulating fluid flow in a casting/molding process generally involve applying the equations of motion, continuity and energy to a discretized model of the molded part and performing numerical calculations thereof to obtain velocity, pressure, and temperature distributions along the processing line. In these simulations, the thermal physical properties of the material, the operational characteristic such as temperature of the material, temperature of the mold and injection speed, etc., are required input for the simulation. These inputs are generally assumptions made based on experimental know-how obtained from repeated comparisons between the analytical results and the actual moldings. The conventional models generally provide no means for determining whether or not input conditions are appropriate. It is therefore necessary to supply realistic boundary conditions before an accurate simulation can be achieved. Conventional fluid flow models lack many refinements which would enable better estimation of the boundary conditions, and hence often fail to achieve an accurate simulation.
One refinement which would be desirable, is incorporating the flow in the shot sleeve into the model. In a traditional die-casting process, molten material is delivered from the reactor to a die through a gated shot sleeve. Pressure is applied via a ram or plunger to eject the molten material from the shot sleeve. Due to discontinuity created by the moving ram and the resulting instability in numerical models, many prior art models start the simulation at the gate entrance and make the assumption that the pressure or velocity applied by the ram is uniform across the gate surface. In addition, prior art simulations assume the fluid contained within the shot sleeve has a uniform pressure and temperature. In practice, the molten metal in the shot sleeve always has some temperature variation, and the pressure applied to the billet across the ram face is non-uniform. More importantly, the thickness and temperature of biscuit remains in the shot sleeve after the cavity is filled has a major effect on the effectiveness of pressurization, which is required to suppress the formation of shrinkage porosity. This non-uniformity of temperature pressure and material flow in the short sleeve, if not corrected, ultimately compromises the accuracy of the mass flux computation of a flow model. Incorporating flow in the shot sleeve as part of the flow model would correct this deficiency.
Another refinement, which would be desirable, is to incorporate the heat exchange between the die and the heat-transfer fluid (HTF) into the model. A process parameter common to all metal die casting or plastic injection molding processes, including semi-solid forming, is the temperature control of the die. The temperature of the die is generally maintained by HTF contained in the heat transfer line which is embedded in the body of the die. Heated oil or water can be used to pre-heat the die to shorten the start-up time and the corresponding scrap. During continuous production, the temperature of the HTF can be adjusted to maintain the cyclic thermal balance in the die. Many attempts have been made to incorporate the heat transfer between the die and the HTF in a flow model. The most vigorous and resource-demanding approach is to use full 3D model to simulate the flow and convection heat transfer of the HTF inside the duct. In order to reduce the computational time, most of the existing models neglect the flow and temperature change of the HTF in the die. Instead, the user is required to select the element surfaces of the heat transfer lines and to assign, as thermal boundary conditions, a HTF temperature and a heat transfer coefficient. Since the HTF's viscosity changes with its temperature, which varies through the entire loop, it is very difficult for the user to determine the coefficient, as the Reynolds number and Prandtl number are not constant. A method which updates the heat transfer coefficient of the HTF as its temperature varies, such that the heat flux from the die to the HTF may be accurately determined, would be desirable.
A method for predicting the formation of shrinkage porosity would also be a desirable feature to be incorporated in a metal casting, e.g. semi-solid forming, simulation model. Shrinkage porosity formation is a common problem for metal casting process. When molten metal fills the cavity in a die which is at a lower temperature than the molten metal, the molten metal loses its thermal energy to the die and begins to solidify. As the liquid phase changes to solid, its density increases. If there is no additional material fed into the cavity, the net volume of the metal will become less than that of the cavity and shrinkage porosity will result. Depending on its size and distribution, shrinkage porosity could compromise the mechanical properties of a product, especially its elongation and fatigue strength, significantly. For pressure tight products, shrinkage porosity may randomly form multiple chained paths and cause leaking. Accurate predictions of shrinkage porosity are essential, when designing a structural component, e.g. control arm and knuckle, and high-pressure housing, e.g. air-conditioner housing and fuel-injection rail.
So far, the state-of-the-art casting simulation programs can only display potential locations of shrinkage porosity based on the hot spots (non-solidified metal surrounded by solidified metal) within the alloy's volume. In addition to temperature distribution, some of the programs also incorporate cooling rate and its empirical correlation to predict shrinkage porosity. However, the formation of shrinkage porosity is actually coupled not just with the thermal factors but also with the flow and pressurization. If the molten material in the cavity is in direct communication with a pressurized liquid metal source, e.g. the remaining liquid metal in the shot sleeve, additional material may be pushed into the cavity to compensate the volume shrinkage and to suppress the formation of shrinkage porosity. The required pressure depends on the viscosity of the solidifying metal, the alloy's temperature and the cavity's geometry. For accurate predictions and hence prevention of the formation of shrinkage porosity, a model that simulates both the thermal variation and the flow of the molten material would be required.
Another feature that is important to any casting or mold filling process is monitoring the cooling of the die after the part is ejected. Generally in a pressure casting process, after the metal solidifies in the cavity, the die opens to eject the part. A water-based lubricant is then sprayed on the mold walls for die release and to prevent drag mark or soldering. As the lubricant typically contains 98% water, it removes most of the thermal energy transferred to the die from the alloy. In order to predict the die temperature and its heat transfer with the alloy, the cooling effects of the lubricant spray in the model must be incorporated. However, due to the severe process conditions, there is no realistic method to determine the die temperature and hence the rate of heat removal by the lubricant. In addition, there are generally multiple nozzles spraying lubricants from different angles. Sometimes, these nozzles may move back and forth to spray lubricant more uniformly. Furthermore, depending on the type of nozzle, distance from the mold surface and spray pressure, the resulting distribution of cooling effects is not uniform. As a result, it is very difficult for user to define the corresponding cooling coefficient on the mold surface, especially one with complex shape. In some of the existing program, the user has to manually select and assign cooling coefficients on those elements surfaces that may be covered by the spray. In cases where that the nozzle moves, it would take too much time to set up the cooling coefficients. A model that computes the cooling efficiency from the geometry of the spray nozzle and its motion would be desirable.
A model to predict the location of a mend line and trapped air would also be a desirable feature for incorporation in a casting or molding simulation. When molten material fills a cavity, the melt front may split, e.g. to go around a core or a hole, and re-join. As the melt front is in contact with die steel and air, it may become too cold and/or contaminated by the residual lubricant or moisture. In addition, if the die is inappropriately designed, the cavity may not be filled progressively and air may be trapped inside the molten metal. As a result, wherever melt fronts meet, the bonding on the interface may be weakened due to solidification, trapped air or impurities.
Although the user can display the filling pattern from various angles to search for mend lines, it is very time consuming and not reliable, especially if the part is large and complicated. Furthermore, after the melt fronts meet, they could continue to move if the cavity was not completely filled. As a result, the final position of the weakened bonding interface may be different from the original mending location. In addition, the strength of bonding could be improved if there is a vigorous mixing of the material across the interface. It is very important in the design stage to be able to identify these potential casting defects quantitatively so that preventive design can be incorporated early in the design stage. Otherwise, the processing window would become very tight and it would be difficult to maintain consistent quality.
Therefore, there is a need for a new method which incorporates the aforementioned refinements such that incompressible, viscous fluid flow behavior in a casting/molding process can be accurately modeled by computer simulations.